{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:W7UYP4MXUVIRVGAPT2LIGWWMPX","short_pith_number":"pith:W7UYP4MX","schema_version":"1.0","canonical_sha256":"b7e987f197a5511a980f9e96835acc7df5581015b6467e5d322c186efe9c9742","source":{"kind":"arxiv","id":"2606.06312","version":1},"attestation_state":"computed","paper":{"title":"Meridian: Metric-Semantic Primitive Matching for Cross-View Geo-Localization Beyond Urban Environments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Camillo Jose Taylor, Carlos Nieto-Granda, Fernando Cladera, Jonathan P. How, Mason Peterson, Qingyuan Li, Yixuan Jia","submitted_at":"2026-06-04T15:52:40Z","abstract_excerpt":"Successful robot automation requires accurate global localization to support repeatability, task planning, goal specification, and safe operation. However, reliable localization in GNSS-denied environments remains an open problem. Overhead aerial imagery offers a promising solution, but existing approaches primarily target structured urban environments and have been rarely demonstrated in unstructured natural terrain. Limitations of the state-of-the-art include a reliance on models trained for specific environments, as well as difficulty handling repetitive geometries and featureless landscape"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2606.06312","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-06-04T15:52:40Z","cross_cats_sorted":[],"title_canon_sha256":"db8ddeadf150e33742cf1b8d0b17f840bae441cb613964ae0add3c04f5f199f3","abstract_canon_sha256":"e729678cdeaca9094581b909e6f38e4c9596aa86ad7f9074bb964d35b189bed3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-05T01:15:41.609050Z","signature_b64":"wK6UgmCQdxXBGNkDMNOIH8QRbPZVb4KiyfWZxW0fBhWqNlo2ZXVx/8GScPZKUKOYM+3HW8pYoovddqCUM5C1Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b7e987f197a5511a980f9e96835acc7df5581015b6467e5d322c186efe9c9742","last_reissued_at":"2026-06-05T01:15:41.608641Z","signature_status":"signed_v1","first_computed_at":"2026-06-05T01:15:41.608641Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Meridian: Metric-Semantic Primitive Matching for Cross-View Geo-Localization Beyond Urban Environments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Camillo Jose Taylor, Carlos Nieto-Granda, Fernando Cladera, Jonathan P. How, Mason Peterson, Qingyuan Li, Yixuan Jia","submitted_at":"2026-06-04T15:52:40Z","abstract_excerpt":"Successful robot automation requires accurate global localization to support repeatability, task planning, goal specification, and safe operation. However, reliable localization in GNSS-denied environments remains an open problem. Overhead aerial imagery offers a promising solution, but existing approaches primarily target structured urban environments and have been rarely demonstrated in unstructured natural terrain. Limitations of the state-of-the-art include a reliance on models trained for specific environments, as well as difficulty handling repetitive geometries and featureless landscape"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.06312","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2606.06312/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.06312","created_at":"2026-06-05T01:15:41.608702+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.06312v1","created_at":"2026-06-05T01:15:41.608702+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.06312","created_at":"2026-06-05T01:15:41.608702+00:00"},{"alias_kind":"pith_short_12","alias_value":"W7UYP4MXUVIR","created_at":"2026-06-05T01:15:41.608702+00:00"},{"alias_kind":"pith_short_16","alias_value":"W7UYP4MXUVIRVGAP","created_at":"2026-06-05T01:15:41.608702+00:00"},{"alias_kind":"pith_short_8","alias_value":"W7UYP4MX","created_at":"2026-06-05T01:15:41.608702+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/W7UYP4MXUVIRVGAPT2LIGWWMPX","json":"https://pith.science/pith/W7UYP4MXUVIRVGAPT2LIGWWMPX.json","graph_json":"https://pith.science/api/pith-number/W7UYP4MXUVIRVGAPT2LIGWWMPX/graph.json","events_json":"https://pith.science/api/pith-number/W7UYP4MXUVIRVGAPT2LIGWWMPX/events.json","paper":"https://pith.science/paper/W7UYP4MX"},"agent_actions":{"view_html":"https://pith.science/pith/W7UYP4MXUVIRVGAPT2LIGWWMPX","download_json":"https://pith.science/pith/W7UYP4MXUVIRVGAPT2LIGWWMPX.json","view_paper":"https://pith.science/paper/W7UYP4MX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.06312&json=true","fetch_graph":"https://pith.science/api/pith-number/W7UYP4MXUVIRVGAPT2LIGWWMPX/graph.json","fetch_events":"https://pith.science/api/pith-number/W7UYP4MXUVIRVGAPT2LIGWWMPX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/W7UYP4MXUVIRVGAPT2LIGWWMPX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/W7UYP4MXUVIRVGAPT2LIGWWMPX/action/storage_attestation","attest_author":"https://pith.science/pith/W7UYP4MXUVIRVGAPT2LIGWWMPX/action/author_attestation","sign_citation":"https://pith.science/pith/W7UYP4MXUVIRVGAPT2LIGWWMPX/action/citation_signature","submit_replication":"https://pith.science/pith/W7UYP4MXUVIRVGAPT2LIGWWMPX/action/replication_record"}},"created_at":"2026-06-05T01:15:41.608702+00:00","updated_at":"2026-06-05T01:15:41.608702+00:00"}